Author

Mingzhe Zhang

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Preprint Aug 2026

Puro-2B: Poor Lab's Qwen2-1.5B Trained on RTX 5090 within $5090

Language model pretraining has become almost synonymous with prohibitive cost, placing it out of reach for much of the academic and open-source communities. Although strong open-source efforts already exist, including open-weight models and open-source training recipes, a cost-efficient, hardware-accessible, and open-s...

Kai-Rong Luo, Jia-Rui Cui, Yao-Rui Yin et al. · 0 citations

#natural language process... Preprint Aug 2026

Puro-2B: Poor Lab's Qwen2-1.5B Trained on RTX 5090 within $5090

This report presents an open pretraining recipe that trains a collection of Puro-2B models from scratch on up to 1.4 trillion tokens with FP8 precision on consumer-grade RTX 5090 GPUs, and derives a Puro Cost Scaling Law that relates training cost to average model performance.

Kairong Luo, Jia-Rui Cui, Yao-Rui Yin et al. · 0 citations